Bayesian Nonparametric Data Analysis / / by Peter Müller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson

• Autore: Müller Peter
• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
• Edizione: 1st ed. 2015.
• Descrizione fisica: 1 online resource (203 p.)
• Disciplina: 519.542
• Soggetto topico: Statistics; Mathematical statistics - Data processing; Biometry; Statistical Theory and Methods; Statistics and Computing; Biostatistics
• Persona (resp. second.): QuintanaFernando Andrés; JaraAlejandro; HansonTim
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index at the end of each chapters.
• Nota di contenuto: Preface -- Acronyms -- 1.Introduction -- 2.Density Estimation - DP Models -- 3.Density Estimation - Models Beyond the DP -- 4.Regression -- 5.Categorical Data -- 6.Survival Analysis -- 7.Hierarchical Models -- 8.Clustering and Feature Allocation -- 9.Other Inference Problems and Conclusions -- Appendix: DP package.
• Sommario/riassunto: This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in on-line software pages.
• Titolo autorizzato: Bayesian Nonparametric Data Analysis
• ISBN: 9783319189680; 3319189689
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910299766803321
• Lo trovi qui: Univ. Federico II
• Serie: Springer Series in Statistics, . 2197-568X